{"title":"Gender dynamics of German journalists on Twitter","authors":"Benedict Witzenberger, Jürgen Pfeffer","doi":"10.1109/ASONAM55673.2022.10068698","DOIUrl":"https://doi.org/10.1109/ASONAM55673.2022.10068698","url":null,"abstract":"Women are underrepresented in many areas of journalistic newsrooms. In this paper, we examine if this es-tablished effect is continued in the new forms of journalistic communication, Social Media Networks. We used mentions and retweets as measures of journalistic amplification and legitimation. Furthermore, we compared two groups of journalists in different stages of development: political and data journalists in Germany in 2021. Our results show that journalists regarded as women tend to favor their peers in mentions and retweets on Twitter: while both professions are dominated by a massive number of men and a high share of men-authored tweets, females mentioned and retweeted other women to a more extensive degree than their male colleagues. In addition, we have found data journalists to be more inclusive towards non-members in their network compared to political journalists.","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124731089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shangce Gao, J. Akaichi, Jijun Tang, Jianxin Wang, Lusheng Wang, Shuliang Wang, O. Maruyama, Jin Huang, Fahad Saeed, W. M. Univ, Doina Caragea, G. Leonardi, Huiyu Zhou, G. Tsihrintzis
{"title":"HI-BI-BI 2022 Organizing Committee","authors":"Shangce Gao, J. Akaichi, Jijun Tang, Jianxin Wang, Lusheng Wang, Shuliang Wang, O. Maruyama, Jin Huang, Fahad Saeed, W. M. Univ, Doina Caragea, G. Leonardi, Huiyu Zhou, G. Tsihrintzis","doi":"10.1109/asonam.2014.6921538","DOIUrl":"https://doi.org/10.1109/asonam.2014.6921538","url":null,"abstract":"","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121367141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Comparative Study of China's Foreign Ministry Spokesperson's Use of Weibo and Twitter","authors":"Zhuo Cheng, Samira Shaikh","doi":"10.1109/ASONAM55673.2022.10068669","DOIUrl":"https://doi.org/10.1109/ASONAM55673.2022.10068669","url":null,"abstract":"Governments around the world are embracing social networks to promote their agendas, and China is no exception. Although Twitter is blocked in China, many diplomats own Twitter accounts and actively post content. Particularly, Zhao Lijian (China's Ministry of Foreign Affairs Spokesperson) is prolific on Twitter as well as its Chinese counterpart, Weibo. This paper examines the entities mentioned in and the sentiment of Zhao's posts, delivered or not delivered to people within China, to study the similarity and differences between his use of Weibo and Twitter. This paper also compares the users' engagement with Zhao on both platforms, exploring the possible factors influencing users' engagement on both platforms.","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130842927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Source Aware Budgeted Information Maximization","authors":"Rithic Kumar N, Y. Gupta, Sanatan Sukhija","doi":"10.1109/ASONAM55673.2022.10068591","DOIUrl":"https://doi.org/10.1109/ASONAM55673.2022.10068591","url":null,"abstract":"The paper proposes a more general framework for budgeted influence maximization. We propose a novel cost function that considers the potential seed nodes' properties and the firm interested in maximizing the influence. A greedy algorithm, maximizing the influence to cost ratio, is then used to select a balanced set of seed nodes. We also show that the edge weights play an important role in determining the influential power of nodes. Further, the edge weights for a network can be efficiently predicted with the help of link prediction heuristics like resource allocation metrics and the Adamic-Adar index.","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117354192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sowmya Balasubramanian, Venkatesh Srinivasan, Alex Thomo
{"title":"Identifying Important Features for Clinical Diagnosis of Thyroid Disorder","authors":"Sowmya Balasubramanian, Venkatesh Srinivasan, Alex Thomo","doi":"10.1109/ASONAM55673.2022.10068712","DOIUrl":"https://doi.org/10.1109/ASONAM55673.2022.10068712","url":null,"abstract":"Abnormal production of thyroid hormones in our body causes thyroid disorders such as hypothyroidism, hyper-thyroidism, Hashimoto's disease, Graves' disease, and thyroid nodules. Undiagnosed thyroid disorders can affect the quality of life of an individual both physically and mentally. Thyroid disorders are common but sometimes become difficult to diagnose since the symptoms can be easily associated with other health conditions. Clinicians identify thyroid disorders by measuring the levels of thyroid hormones in our blood stream. This work aims to help clinicians by carefully investigating if thyroid diagnosis improves when all important features (a complete thyroid panel) is measured as opposed to a select few. Much of previous work has focused on the performance of classifiers, supervised and unsupervised, for the prediction of this disorder. Departing from this tradition, we focus on the concept of feature importance and its clinical implications. We identify the top-4 important features that predict the presence of thyroid disorder and show that these can be measured by clinicians cost-effectively. We also identify the pitfalls of current clinical practice of not checking the entire thyroid panel, prevalent in many countries with universal health care. Finally, we show that our results are quite robust and are unlikely to change with the choice of classifier or due to the inherent nature of a dataset in hand like imbalance.","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128863385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"FAB 2022 Symposium Organizing Committee","authors":"","doi":"10.1109/asonam.2016.7752194","DOIUrl":"https://doi.org/10.1109/asonam.2016.7752194","url":null,"abstract":"","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132963796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Diachronic Analysis of Users' Stances on COVID-19 Vaccination in Japan using Twitter","authors":"Shohei Hisamitsu, Sho Cho, Hongshan Jin, Masashi Toyoda, Naoki Yoshinaga","doi":"10.1109/ASONAM55673.2022.10068695","DOIUrl":"https://doi.org/10.1109/ASONAM55673.2022.10068695","url":null,"abstract":"To prevent and curb viral outbreaks, such as COVID-19, it is important to increase vaccination coverage while resolving vaccine hesitancy and refusal. To understand why COVID-19 vaccination coverage had rapidly increased in Japan, we analyzed Twitter posts (tweets) to track the evolution of people's stance on vaccination and clarify the factors of why people decide to vaccinate. We collected all Japanese tweets related to vaccines over a five-month period and classified the vaccination stances of users who posted those tweets by using a deep neural network we designed. Examining diachronic changes in the users' stances on this large-scale vaccine dataset, we found that a certain number of neutral users changed to a pro-vaccine stance while very few changed to an anti-vaccine stance in Japan. Investigation of their information-sharing behaviors revealed what types of users and external sites were referred to when they changed their stances. These findings will help increase coverage of booster doses and future vaccinations.","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131651489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Ting, Chia-Sung Yen, Chia-Chun Kang, Shuang Yang
{"title":"An Empirical Study of Automatic Social Media Content Labeling and Classification based on BERT Neural Network","authors":"I. Ting, Chia-Sung Yen, Chia-Chun Kang, Shuang Yang","doi":"10.1109/ASONAM55673.2022.10068630","DOIUrl":"https://doi.org/10.1109/ASONAM55673.2022.10068630","url":null,"abstract":"Web flow now is a very important success factor for social media marketing and thus more and more approaches for creating high web flow have been proposed in recent years. Automatic content generation (ACG) website is one of the possible approaches which can help to create web flow. In order to achieve the idea of automatic content generation website, web article classification has been considered the most important task. Therefore, we have development an empirical study to test the content labeling and article classification performance, which is based on the technique of BERT neural network. The performance evaluation including accuracy performance and time performance that are important for us to understand the possibility for implementing the ACG website in real environment, especially the possibility when dealing with large amount of data.","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"385 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133168001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"TSPA: Efficient Target-Stance Detection on Twitter","authors":"Evan M. Williams, K. Carley","doi":"10.1109/ASONAM55673.2022.10068608","DOIUrl":"https://doi.org/10.1109/ASONAM55673.2022.10068608","url":null,"abstract":"Target-stance detection on large-scale datasets is a core component of many of the most common stance detection applications. However, despite progress in recent years, stance detection research primarily occurs at the document-level on small-scale data. We propose a highly efficient Twitter Stance Propagation Algorithm (TSPA) for detecting user-level stance on Twitter that leverages the social networks of Twitter users and runs in near-linear time. We find TSPA achieves SoTA accuracy against BERT, homogenous Graph Attention Networks (GAT), and heterogenous GAT baselines. Additionally, TSPA's wall-clock time was 10x faster than our best baseline on a GPU and over 100x faster than our best baseline on a CPU.","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132800149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"ASONAM 2022 Organizing Committee","authors":"","doi":"10.1109/asonam55673.2022.10068689","DOIUrl":"https://doi.org/10.1109/asonam55673.2022.10068689","url":null,"abstract":"","PeriodicalId":423113,"journal":{"name":"2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130053806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}